@article{fdi:010087710,
  title = {{C}omparison of near and mid-infrared reflectance spectroscopy for the estimation of soil organic carbon fractions in {M}adagascar agricultural soils},
  author = {{R}amifehiarivo, {N}andrianina and {B}arth{\`e}s, {B}ernard and {C}ambou, {A}ur{\'e}lie and {C}hapuis {L}ardy, {L}ydie and {C}hevallier, {T}iphaine and {A}lbrecht, {A}lain and {R}azafimbelo, {T}.},
  editor = {},
  language = {{ENG}},
  abstract = {{A}ssessing the different pools of soil organic carbon ({SOC}) improves our understanding of how and at what rate the different forms of carbon ({C}) are being formed or lost in soils. {P}hysical fractionation of soil organic matter ({SOM}) has often been used to separate and quantify {SOC} pools, but this approach is very tedious and can rarely be performed on large sample sets. {I}nfrared spectroscopy has proven useful for time-and cost-effective quan-tification of total {SOC}, which prompted us to study its ability to characterise the distribution of {SOC} in physical fractions. {T}his study aimed to compare the potential of near-and mid-infrared reflectance spectroscopy ({NIRS} and {MIRS}, respectively) to predict the distribution of {SOC} in particle-size and particle-density fractions, using spectra of unfractionated soils. {A} set of 134 sieved (< 2 mm) soil samples originating from seven sites in con-trasting pedoclimatic regions of {M}adagascar was studied. {F}or each sample, five {SOM} fractions were separated: the particulate organic matter fraction ({POM}) and the particle-size fractions >200 mu m, 50-200-mu m, 20-50-mu m and < 20 mu m. {T}he mass (g fraction 100 g(-1) soil), {SOC} concentration (g{C} kg(-1) fraction) and {SOC} amount (g{C} fraction kg(-1) soil) were determined for each fraction in the laboratory. {T}he {NIR} and {MIR} spectra were acquired on finely ground (< 0.2 mm) aliquots of unfractionated soil. {T}hen, spectra were used for the prediction of each variable (i.e., the mass, {SOC} concentration and amount of each fraction, and {SOC} content of unfractionated soil), which was achieved with locally weighted partial least squares regression ({LW}-{PLSR}) on {NIRS} and {MIRS} data separately. {F}or both spectral ranges, the same samples were used for calibration (n = 109, selected for spectral representativeness) and validation (n = 25). {M}odels based on {NIRS} and {MIRS} yielded excellent predictions for {SOC} content in unfractionated soil ({R}-2 = 0.98 and ratio of performance to interquartile range {RPIQ} >= 13) and accurate predictions ({R}2 >= 0.75 and {RPIQ} >= 2) for the mass, {SOC} concentration and {SOC} amount in most fractions. {T}he predictions of {SOC} concentrations and {SOC} amounts were better in the fractions <200 mu m ({R}-2 >= 0.85 and {RPIQ} >3), especially in the fraction <20 mu m ({R}-2 > 0.9 and {RPIQ} >4.5). {I}n most cases, {NIRS} slightly outperformed {MIRS}. {T}his result contradicts most previous studies performed on soils from temperate regions but confirms those performed on soils from tropical regions.{I}nfrared spectroscopy allowed accurate prediction of {SOC} distribution in particle-size fractions, which paves the way to high-throughput characterization of {SOM}.},
  keywords = {{S}oil fractionation ; {L}ocally weighted {PLSR} ; {I}nfrared reflectance ; spectroscopy ; {S}oil organic matter ; {T}ropical soils ; {F}erralsols ; {A}renosols ; {F}luvisols ; {MADAGASCAR}},
  booktitle = {},
  journal = {{G}eoderma {R}egional},
  volume = {33},
  numero = {},
  pages = {e00638 [13 ]},
  ISSN = {2352-0094},
  year = {2023},
  DOI = {10.1016/j.geodrs.2023.e00638},
  URL = {https://www.documentation.ird.fr/hor/fdi:010087710},
}